The present invention relates to method and an apparatus for determining dimensional and/or geometric characteristics of a measurement object.
Determining dimensional and/or geometric characteristics of an object is a typical task in industrial metrology. By way of example, geometric and/or dimensional characteristics of an individual workpiece are determined for quality control in industrial production processes in order to check whether the workpiece observes specified tolerances. In the development and design of new products, it is also frequently desirable to measure the individual characteristics of a prototype or of a counterpart that cooperates with the workpiece to be designed. The dimensional and/or geometric characteristics can include distances between individual features of the workpiece, such as the distance between two edges or the diameter of a hole, and also the complex geometric shape of the workpiece. Increasingly there has been a desire to obtain what is known as a 3D scan of a workpiece or a workpiece part. The 3D scan provides a plurality of spatial coordinates (3D coordinates), which define the position of numerous measurement points on the workpiece relative to a reference coordinate system and which therefore describe the complex shape of the workpiece. The dimensional and/or geometric characteristics can be determined on the basis of the measured spatial coordinates.
There are various methods for obtaining a 3D scan of a workpiece or measurement object. By way of example, a probe element can be used to physically touch the desired measurement points, wherein the spatial coordinates of the measurement points are determined from the respective position of the calibrated probe element relative to the reference coordinate system. In addition, there are various contactless methods for determining the position of measurement points relative to a reference coordinate system. Some methods are based on triangulation, in which the measurement object is recorded with one or more cameras and the evaluation of the camera images is based on trigonometric relationships. In some of these methods, the measurement object is illuminated with a defined pattern, for example in the case of what is known as fringe projection method. Each method has specific advantages and disadvantages with respect to the apparatus involved and with respect to the size of the measurement volume, the attainable measurement accuracy, measurement velocity, and others. For example, fringe projection methods are sensitive with respect to image noise and are not suitable for high-gloss surfaces.
A publication by R. J. Woodham with the title “Photometric Method for Determining Surface Orientation from Multiple Images”, published in Optical Engineering, 19(1), 1980, describes a method with which the respective local orientation of the measurement object surface can be determined at a plurality of measurement points by illuminating the surface successively from different directions. Using a stationary camera, images of the respectively illuminated surface are recorded and what are known as the surface normals are determined therefrom. A surface normal is a vector which is perpendicular to the surface and consequently represents the orientation of the surface at that location. The method by Woodham is known by the term photometric stereo and is based on the assumption of point-like light sources, situated at infinity, with in each case the same light intensity. This assumption cannot be met in practice, which results in measurement errors when determining the surface normals.
A publication by Diego Nehab et al. with the title “Efficiently Combining Positions and Normals for Precise 3D Geometry”, ACM Transactions on Graphics (Proc. of ACM SIGGRAPH 2005) proposes a computational combination of the measurement results from a fringe projection method and from a photometric stereo method. The surface normals of the measurement object can be calculated using the 3D coordinates from the fringe projection method. Vice versa, it is possible to reconstruct the object surface on the basis of the surface normals from photometric stereo, and 3D coordinates therefrom. Fringe projection methods result in rather short-wave/high-frequency measurement errors (with respect to the extent of the surface) in the form of apparently random, high-frequency noise. By contrast, measurement errors in the case of photometric stereo are rather longwave. Nehab et al. propose to combine by calculation the “good” measurement results of the fringe projection method in the long-wave range with the “good” measurement results of the photometric stereo method in the short-wave/high-frequency range. The object surface is alleged to be reconstructed in a more detailed and more accurate manner in this way than by each individual method.
Moreover, many other proposals exist for increasing the accuracy of a metrological reconstruction of an object surface. For example, Mohit Gupta et al. propose in a publication with the title “A Practical Approach to 3D Scanning in the Presence of Interreflections, Subsurface Scattering and Defocus”, published in the International Journal of Computer Vision 102.1 to 3 (2013), the use of specific projection patterns for a fringe projection method to better control multiple reflections, scattering at depth (subsurface scattering) and focusing errors. Two further publications discuss improvements in the use of spatially near point light sources for photometric stereo, namely Woyuan Xie et al. “Photometric Stereo with Nearpoint Lighting: A Solution by Mesh Deformation”, published in IEEE Conference of Computer Vision and Pattern Recognition (CVPR) and Thoma Papadhimitri et al. “Uncalibrated Near-Light Photometric Stereo”, published in Proceedings of the British Machine Vision Conference 2014.
DE 10 2010 007 396 A1 discloses a method and an apparatus for optically inspecting a measurement object having an at least partially reflective surface in order to determine the local scattering characteristics of the object surface. In this method, the object surface is successively illuminated with light sources at different positions, similar to the photometric stereo method. A camera takes a series of images with the different illuminations. Subsequently, an individual light origin region is determined for at least one camera pixel. The light origin region represents the spatial distribution of the individual light contributions produced by the individual light sources over the surface of the measurement object on the at least one pixel. Next, the scattering characteristics of the surface point recorded by the camera pixel is determined on the basis of the individual light origin region. 3D coordinate measurement and determination of dimensional and/or geometric characteristics of the measurement object which is based thereon is not envisaged in this method.